Serverless Computing

Tired of paying the "container tax" for bursty, event-driven workloads? It's time to elevate your cloud architecture. Building Serverless Applications with WebAssembly & Spin walks you through constructing a robust, multi-component Rust app from scratch. You will master Spin, learn about the underlying Wasm Component Model, and ship your app seamlessly to both Kubernetes and edge runtimes. Ditch heavy base images, eliminate cold starts, and master the future of lightweight, secure serverless compute.

In this book, one estate runs through all fourteen chapters. There are eight services across two regions, a hybrid link to an older data centre, a storefront that real customers use, and one service backed by a language model. We use OpenObserve for that, bring all the signals into it, shape the data until long-term storage becomes affordable, and then spend the rest of the time diagnosing the estate when it breaks. There won't be a feature tour here. The features don't stand the test of time, and the screenshots are even worse. What you'll find is a method. First, scope the flag, orient before acting, form a hypothesis you can disprove, test it against evidence rather than instinct, repair, verify, and add the prevention that stops the same failure twice. That loop works whatever platform you use.

"Unlock the Secrets of GCP Networking!Design secure, scalable, and high-performance cloud networks with VPC and Subnetwork Designing in GCP. From subnet planning to hybrid connectivity, this guide empowers you to master GCP’s networking backbone—whether you're migrating, scaling, or certifying. Your cloud’s foundation starts here."

Build the Next Generation of Enterprise AI SystemsCloud-Powered Agentic AI is a practical guide to designing, developing, deploying, and operating production-ready AI applications using Large Language Models (LLMs) and modern cloud-native technologies.From prompt engineering and Retrieval-Augmented Generation (RAG) to AI agents, multi-agent systems, Model Context Protocol (MCP), FastAPI, Docker, Kubernetes, and LLMOps, this book provides a complete roadmap for building scalable, secure, and maintainable AI solutions.Through hands-on examples, architecture diagrams, case studies, and a comprehensive capstone project, you will learn how to move beyond prototypes and engineer enterprise-grade AI systems.Inside this book, you'll learn how to:Build LLM-powered applications from scratchDesign Retrieval-Augmented Generation (RAG) pipelinesDevelop AI agents and multi-agent workflowsIntegrate tools using the Model Context Protocol (MCP)Deploy AI services with FastAPI, Docker, and KubernetesApply LLMOps for monitoring, evaluation, and continuous deliverySecure and govern AI applications in enterprise environmentsBuild a complete cloud-native AI platform from development to productionWhether you are an AI engineer, software developer, cloud architect, or machine learning practitioner, this book will equip you with the practical skills needed to build reliable and scalable AI systems in the era of generative AI.

A GPU inference service on Azure that costs nothing while idle. Real billing data from 48 days in production, plus every trap that cost me time getting there.

The ultimate practical guide designed to fast-track your technical skills without the fluff. Whether you are a developer, student, or DevOps engineer, this essential reference delivers actionable insights to solve real-world problems instantly. Master your craft and stream-line your workflow today!

Deploy Python applications without managing servers. This practical guide takes you from your first serverless function to production-ready architectures on AWS Lambda and Cloudflare Workers using the Serverless Framework. Through real-world examples, proven deployment patterns, and hands-on guidance, you will learn how to build scalable, secure, and cost-effective applications with confidence.